Recreate a real-world hospital setting with superior patient-doctor interaction and a well-organised network of carers all under one roof. It has never been so simple to set up a research team on Dockare.
Data collected digitally at source, with no manual transcription and hand-offs coupled with intelligent validations drive data to be of high quality and reliability. Increases the quality of insight generation. Stage-gated quality checks using advanced ML algorithms help achieve high levels of specificity and accuracy.
Transform your study objectives and clinical endpoints to intuitive e-CRFs. Our e-CRFs are easily created and validated for accurate data collection and effective execution of RWE studies. Pick from out-of-the box templates using a wizard directed across purpose and therapeutic areas to quickly deploy these forms.
Our platform is designed on global standards of HL7 and FHR data structure making you ready for standard data import and export. Widening your data architecture across EHRs, clinical and multiple other disparate patient data sources making it wider, deeper and richer for generating high quality insights.
Dockares’ data structure is well-organised, making analysis less cumbersome, reducing cleaning efforts and providing our data scientists to look farther into outcomes. Dockares’ market-ready analytic plan allows you to reach insights faster and solving your complex business challenges with ease.
Over 100+ years of collective experience of our cross-functional team across clinical, hospital, regulatory, payer HTA assessors and clinical scientists makes Dockare to transform your strategies to reality by providing pointed insights and specific evidences to fulfil your business objectives.
Real-world Evidence (RWE) studies
Registries and outcome research
Smart & adaptive study designs
Technology-enabled e-platform
Intelligent data insights
Accelerated publications
Consider gathering pertinent real-world evidence from unlimited access to millions of anonymized patient records in addition to regulatory, clinical, and development data to fuel your commercialization efforts. Join forces with our consulting team to identify the most economical way to hasten product approval, improve prescriptions, and expand market access with our services.
Investigators can deploy their studies on Dockare platform for the collection of IIS data across their study site. Once the study is completed, analytics, reporting including publication of the study will be undertaken by Dockare’s team.
Designing outcomes-based studies for any purpose-healthcare practice, treatments, surgical or other interventions that impact patient’s experienced end-result within the healthcare systems, can be achieved seamlessly on the Dockare platform.
Generate evidence of therapeutic benefits for newer indications and convert off-label use to labelled products by conducting various research initiatives. RWE for Label expansion includes collation of patient data, analysing, and publishing various types of scientific articles – case studies, series and review articles using Dockare’s services.
EMRs with a large pool of clinical grade data are harnessed to identify participants and enrol them through secure messaging (SM) into RWE studies. Dockare achieves this by keeping the end in mind and accurately identifying the patients qualifying to be a part of the study population.
Dockare uses multi-dimensional analysis using the Hybrid data models for RWE studies conducted for generating clinical effectiveness. This data model is designed using various attributes such as data types, constraints, relationships, and metadata definitions for the data to be queried and extracted from a research database.
Emerging medical and surgical methods need constant upgrades of standards of care, continuously re-evaluating the care systems by performing Standards of Care (SoC)-based studies to examine a new SOC versus an existing standard. Dockare’s platform is intuitive in providing comparative insights between clinical endpoints across the various standards of care.